---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./500
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# ./500

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 500 SF 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6792
- Wer Ortho: 31.5962
- Wer: 21.0621

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 800
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 1.6525        | 3.1746  | 100  | 1.1367          | 40.1968   | 29.4223 |
| 0.8573        | 6.3492  | 200  | 0.7964          | 30.8309   | 20.3803 |
| 0.6108        | 9.5238  | 300  | 0.7344          | 28.6808   | 18.9092 |
| 0.4957        | 12.6984 | 400  | 0.7017          | 29.1181   | 18.7298 |
| 0.4164        | 15.8730 | 500  | 0.6860          | 29.2274   | 18.8016 |
| 0.3577        | 19.0476 | 600  | 0.6802          | 29.3367   | 18.6939 |
| 0.3168        | 22.2222 | 700  | 0.6787          | 31.2682   | 20.7750 |
| 0.3023        | 25.3968 | 800  | 0.6792          | 31.5962   | 21.0621 |


### Framework versions

- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1